Top 6 database and data structure mistakes to avoid

A database design done right, backend managers would face little trouble in the subsequent development, analytics deployment and the overall performance of the insights. However, along the way, database designers do several small but serious mistakes that affect the performance reports of managers, developers and the DBAs. While no list of mistakes is completely exhaustive, everyone does a lot of stupid things to get things done ‘in a hurry’. Listing 6 such mistakes:

1. Poor planning / designing

A good database is so much like designing a house. Built with forethought, it demands a strong but flexible foundation. Like a home cannot be designed without a blueprint in place, database designing also requires complete mapping. This map would integrate your plans and its schematic diagrams and how each of the elements is going to interact with each other. Poor planning is often the reason why databases leave loopholes to be hacked.

2. Ignored normalization

Normalization can be defined as a set of methods that breaks down the database until each element (table in this case) represents a single thing. The concept of normalization is nothing new and has been here for probably more than 30 years. It is also at the core of SQL and other rational database structures. Normalization of database is essential to ensure the best performance and developmental ease.

3. Poor naming standards

If you have worked on Adobe Photoshop, you should know how easy it becomes once you rename your layers individually to identify the elements integrated into it. Naming standard are a popular choice but are also among the most ignored aspects of database designing. Naming allows both present and future programmers to easily understand what each component was intended to be and the type of data it stores. Subsequently, a future programmer wouldn’t have to scan through a 500 page document to do a minor edit or update.

4. Lack in documentation

Proper naming standard should also be supported by through definitions of all tables, columns, the relationships established and the constraints. Again, it makes any programmer working on the design understand how each element as intended to be used. The goal of documentation should be to provide enough information for anyone dealing and trying to understand the design.

5. Single table for all domain values

Many a times, we don’t quite exploit the flexibility of database systems. Crowding a single table with all domain elements makes the database claustrophobic and makes rooms for mistakes. Rational database architecture integrates more tables just to lower the complexities of the design

6. Ignoring SQL facilities to leverage data integrity

A rational database engine should be implemented with all the non-changing and fundamental rules. SQL offers several ways to import data into the server. Defining the basic rules will ensure that they will not be bypassed and the overall structure adheres to the standard norms of your processes.

A good database and data structure should be simple yet strongly protected and defined. Now that every business runs on information, getting loose with the design can cost too much.

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About Ravi Sharma; 

Sales Head - BD @ GirnarSOFT, A $300 Million valued IT company.

I help businesses to build:
✔ Their better connectivity with their existing customers
✔ Helping them finding new customers
✔ Process improvement with better solutions
✔ Digital branding to attract new markets
✔ A better LIFE !!!

To find out more about how I can help you, contact me:

✉ CONTACT Ravi Sharma
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Skype: girnar.sales

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